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ovarian cancer. The laboratory has about 18 members that study ovarian cancer biology. We use a variety of cutting-edge methods, including spatial proteomics, spatial metabolomics, 3D organotypic cultures
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to climate change and variability Hydrological processes in organosols and peat-affected soils Modeling Hydrological Extremes Using Machine Learning Spatial and time distribution of precipitation within
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Assistant Professor in Marine Biology & Ecology - Biomedical Science or Quantitative Systems Ecology
ecologist working in coastal systems, who applies modern approaches in causal inference, experimental ecology, spatial modelling, and data science, including the use of machine learning to produce rigorous
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heterogeneity in head and neck cancers (squamous cell carcinoma, salivary gland cancers, and other tumors). We have advanced the application of single cell sequencing and spatial technologies to rigorously pursue
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creating positive relationships with internal and external contracts. Responsibilities: -Staff Support: Provide office support for select division staff (Forest Analytics - FANA, Spatial Solutions - SPSO and
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community; support multi‑omics data integration and analysis across multiple research groups; and collaborate on the development and maintenance of computational pipelines for spatially resolved
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translational model systems. The research environment provides access to state-of-the-art facilities in genome editing, biological mass spectrometry, advanced imaging, spatial transcriptomics, and 3D
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or the vibrational transitions of a material, to the spatially confined electromagnetic field of an optical resonator. Most importantly, this occurs even in the dark because the coupling involves the zero-point
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“Enhancing Machine Learning Approaches for Spatially Dependent Data in Fisheries and Environmental Research” (CMAT, University of Minho), reference 2024.15617.PEX, financed by national funds through
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project EXPULSE investigates how urban expulsion regimes shape housing trajectories among low-income residents, urban citizenship, and socio-spatial inequalities in four European cities: Brussels, Amsterdam